Geographic Information Systems:

Theory and Practice – 2008 Draft Syllabus

(updated March 2, 2008) 

 

Instructor:  Gregory Stewart

 

Textbook:  GIS Fundamentals, 2nd Ed by Paul Bolstad  (required)

 

Prerequisites:  This is a computer intensive class and we will cover a large amount of material.  Students must be proficient with file management under Windows OS, but no previous experience with GIS is required.

 

Meeting times: The class will meet from 6-10 on Tuesday nights in the Computer Applications Lab (CAL).  Assignments will require use of the CAL during non-class hours.

 

Attendance:  Given the fast pace, students must be prepared to attend all classes and participate with a high level of engagement. 

 

Software:  We will use ArcGIS 9.2 running under WindowsXP.  Students are recommended to use the CAL computers as much as possible, though student copies will be made available.  This software is not supported on Linux or Mac OS and is not yet fully supported under Vista.

 

Homework:  This course will be largely paperless.  Course materials will be handed out electronically and students will be expected to turn in assignments electronically.  Late work not accepted without prior consultation. Due dates will be posted in the course Moodle site, generally Sunday night after class.

 

Collaboration: Student collaboration is highly encouraged but each student must produce his or her own work.  Copying others work will result in no credit.

 

Credit: Students wishing upper division credit will be asked to do incorporate spatial analyses into their final map project.  Projects and analyses must be instructor approved.

 

 

 

Schedule

Week 1- Introduction and Overview of Geographic Information Systems  

Lecture: Definition of GIS, features and functions; why GIS is important; how GIS is used; GIS as an Information System; GIS and cartography; contributing and allied disciplines; introduction to ESRI’s GIS products.

Practicum: Simple mapping exercises.

Reading:  Chapter 1 – An introduction to GIS

 

Week 2– Data Models and Map Elements

Lecture:  Concept of data model; vector, raster, and TIN data models; topology; compression; map design and map elements

Practicum: Mapping using raster and TIN data models, incorporating predefined map elements.

Reading:  Chapter 2 – Data models

 

Week 3– Map Projections and Coordinate Systems

Lecture: Maps and their characteristics (selection, abstraction, scale, etc.); map projections; and coordinate systems; map production.

Practicum: Coordinate transformations, dataset projection.

Reading:  Chapter 3 – Map Projections and Coordinate Systems

 

Week 4– Data Sources, GIS and Maps

 Lecture: Data feeds to GIS and their characteristics: maps, GPS, images, databases, commercial data; locating and evaluating data; data formats; data quality; metadata.

 Practicum:  Creating GIS data using outside data sources including digitization and GPS data, metadata documentation.

 Reading:  Chapter 4 – Data sources and entry

  

Week 5 – Putting together a GIS Dataset and Analysis

 Lecture:  During week 5, we’ll jump ahead and start outlining a final project for the term.  The project will involve gathering data from multiple sources and putting them together with maps that can be served up via the web or intranet and consumed by others.

 Practicum:  User created datasets and maps

 Reading:  Skim Chapters 5-7

 

 Week 6 –  Database Concepts

 Lecture: Database concepts and components; relational databases; databases and GIS; spatial queries.

 Practicum: Database links and queries.

 Reading:  Chapter 8 – Attribute data and tables

 

 Week 7 – Basic Spatial Analyses

 Lecture: Questions only a GIS can answer; GIS analytical functions, map algebra, classification, buffering, overlays.

 Practicum: Spatial queries involving buffers and overlays

 Reading:   Chapter 9 – Basic spatial analysis

 

 Week 8– Raster and Terrain Analysis

 Lecture: Using raster datasets for terrain analysis, working with DEMs, spatial interpolation.

 Practicum: Spatial analysis and 3D tools.

 Reading:  Chapter 10 & 11 – Topics in raster analysis & Terrain analysis

 

 Week 9 – Data Modeling

 Lecture: GIS for GIS users, process modeling, creating macro’s. 

 Practicum: Data modeling in GIS using model builder.

 Reading:  Chapter 13 – Spatial models and modeling

 

Week 10- Lab practical and final project reviews.